Competency: Tallies, tabulates, and prepares data for data analysis.

Classification and Tabulation of Data

The collected data is usually contained in schedules and questionnaires. But that is not in an easily assailable form. The answers will require some analysis if their salient points are to be brought out. As a rule, the first step in the analysis is to classify and tabulate the information collected, or, if published statistics have been employed, rearrange these into new groups and tabulate the new rearrangement. In case of some investigations, the classification and tabulation may give such a clear picture of the significance of the material that no further analysis is required. In other cases, though processes may materially assist the analysis, they are not sufficient to present the facts. They are, however, very important whether they have been very carefully drawn up and the answers may be both complete and accurate, but until these answers are all brought together into the class to which they belong and the whole information displayed in a tabular form, no one will be a great deal wiser as to the contents of the replies.

Although the phase classification and tabulation has been used, classification is, in effect, only the first step in tabulation, for, in general, items having common characteristics must be brought together before the data can be displayed in tabular form.

Some of its main topics are:

1. chronological classification

2. formation of a discrete frequency distribution

3. parts of a table

4. Quantitative classification

5. relative frequency distribution

6. types of tables

Types of Statistical Classifications

Chronological Classification

When data are observed over a period of time, the type of classification is known as chronological classification. For example, we may present the figures of the population (or production, sales. etc.) As follows

Time series are usually listed in chronological order, normally starting with the earliest period. When the major emphasis falls on the most recent events, a reverse time order may be used.

Quantitative Classification

Quantitative classification refers to the classification of data according to some characteristics that can be measured, such as height, weight, income, sales, profits, production, etc. for example, the students of a college may be classified to weight as follows:

Such a distribution is known as empirical frequency distribution or simple frequency distribution.

In this type of classification, there are two elements, namely: (i) the variable, i.e., the weight in the above example, and (ii) the frequency, i.e., the number of students in each class. Fifty students have a weight ranging from 90 to 100 lb, 200 students having a weight ranging from 100 to 110 lb, and so on. Thus we can find out the ways in which the frequencies are distributed.

Parts of a Table

The number of parts varies from case to depending upon the given data. However, the main parts of a table, in general, are discussed here.

Table number - each take should be numbered. There are different practices with regard to the place where this number is to be given. The number may be given either in the center at the top above the title or inside of the title at the top or at the bottom of the table on the left-hand side. However, if space permits, the table number should be given in the center as is shown in the specimen table give on-page. When there so that easy reference to it is possible.

Title of the table - every table must be given a suitable title. The title is a description of the contents of the table. A complete title has to answer the question of what, where, and when in that sequence. In other words:

a) What precisely are the data in the table (i.e.) what categories of statistical data are shown?

b) Where the data occurred 9i.e. the precise geographical, political, or physical area covered)?

c) When the data occurred (i.e., the specific time or period covered by the statistical materials in the table)?

Caption - caption refers to the column headings. It explains what the column represents it may consist of one or more column headings. Under a column heading, there may be sub-heads. The caption should be clearly defined and placed in the middle of the column if the different columns are expressed in different units. The units should be mentioned with the captions. As compared with the main part of the table, the caption should be shown in smaller letters. This helps in saving space.

Stub – as distinguished from the caption, studs are the designations of the rows or row heading. They are at the extreme lift and perform the same function for the horizontal rows of numbers in the table as the column headings do for the vertical columns of numbers. The stubs are usually wide than column headings but should be kept as narrow as possible without sacrificing precision and clarity of statements.

Body - the body of the table contains numerical information. This is the most vital art of the. Data presented in the body arranged according to description are classifications of the captions and studs.

Head note - it is a brief explanatory statement applying to all or a major part of the material in the table and is placed below the point centered and enclosed in brackets. It is used to explain certain points relating to the whole table that have not been included in the title nor the cations or studs. For example, the unit of measurement is frequently written as a head note, such as ''in thousands'' or ''in a million tonne3s or ''in crores'', etc.

Footnotes - anything in a table which the reader may find it difficult to understand from the title, captions and studs should be explained in footnotes. If footnotes are needed, they are placed directly below the body of the table. Footnotes are used for the following main purposes:

a) To points out any exceptions as to the basis of arriving at the data

b) Any special circumstances affecting the data, for example, strike, lock-out fire, etc.

c) To clarify anything in the table

d) To give the source in case of secondary data.